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Python SciPy – ndimage.spline_filter1d() function

  • Last Updated : 21 Jul, 2021

This method is used to calculate a 1-D spline filter along the given axis. These are filtered by a spline filter.

Syntax: scipy.ndimage.spline_filter1d(input, order=3, axis=-1, output=<class ‘numpy.float64’>)

Parameters

input: array_like – The input array

order: int – The order of the spline, default is 3.



axis: int,  – The axis along which the spline filter is applied. Default is the last axis.

output: ndarray  – The array in which to place the output, or the dtype of the returned array. Default is numpy.float64.

Example 1:

Python3




# importing spline filter with one dimension.
from scipy.ndimage import spline_filter1d
 
# importing matplot library for visualization
import matplotlib.pyplot as plt
 
# importing munpy module
import numpy as np
 
# creating an image
geek_image = np.eye(80)
 
# returns an image array format
geek_image[40, :] = 1.0
print(geek_image)

 
 Output:

 

 



Example 2:

Python3




# importing spline filter with one dimension.
from scipy.ndimage import spline_filter1d
 
# importing matplot library for visualization
import matplotlib.pyplot as plt
 
# importing munpy module
import numpy as np
 
# creating an image
geek_image = np.eye(80)
 
geek_image[40, :] = 1.0
 
# in axis=0
axis_0 = spline_filter1d(geek_image, axis=0)
 
# in axis=1
axis_1 = spline_filter1d(geek_image, axis=1)
 
f, ax = plt.subplots(1, 3, sharex=True)
 
for ind, data in enumerate([[geek_image, "geek_image original"],
                            [axis_0, "spline filter in axis 0"],
                            [axis_1, "spline filter in axis 1"]]):
    ax[ind].imshow(data[0], cmap='gray_r')
     
    # giving title
    ax[ind].set_title(data[1])
 
    # orientation layout of our image
plt.tight_layout()
 
# to show image
plt.show()

 
 Output:

 

 

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